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Precision DNA/gene replacement is a promising genome-editing tool that is highly desirable for molecular engineering and breeding by design. Although the CRISPR/Cas9 system works well as a tool for gene knockout in plants, gene replacement has rarely been reported. Towards this end, we first designed a combinatory dual-sgRNA/Cas9 vector (construct #1) that successfully deleted miRNA gene regions ( MIR169a and MIR827a ). The deletions were confirmed by PCR and subsequent sequencing, yielding deletion efficiencies of 20% and 24% on MIR169a and MIR827a loci, respectively. We designed a second structure (construct #2) that contains sites homologous to Arabidopsis TERMINAL FLOWER 1 ( TFL1 ) for homology-directed repair (HDR) with regions corresponding to the two sgRNAs on the modified construct #1. The two constructs were co-transformed into Arabidopsis plants to provide both targeted deletion and donor repair for targeted gene replacement by HDR. Four of 500 stably transformed T0 transgenic plants (0.8%) contained replaced fragments. The presence of the expected recombination sites was further confirmed by sequencing. Therefore, we successfully established a gene deletion/replacement system in stably transformed plants that can potentially be utilized to introduce genes of interest for targeted crop improvement.

Summary The RNA‐guided Cas9 system is a versatile tool for genome editing. Here, we established a RNA‐guided endonuclease (RGEN) system as an in vivo desired‐target mutator (DTM) in maize to reduce the linkage drag during breeding procedure, using the LIGULELESS1 (LG1) locus as a proof‐of‐concept. Our system showed 51.5%–91.2% mutation frequency in T0 transgenic plants. We then crossed the T1 plants stably expressing DTM with six diverse recipient maize lines and found that 11.79%–28.71% of the plants tested were mutants induced by the DTM effect. Analysis of successive F2 plants indicated that the mutations induced by the DTM effect were largely heritable. Moreover, DTM‐generated hybrids had significantly smaller leaf angles that were reduced more than 50% when compared with that of the wild type. Planting experiments showed that DTM‐generated maize plants can be grown with significantly higher density and hence greater yield potential. Our work demonstrate that stably expressed RGEN could be implemented as an in vivoDTM to rapidly generate and spread desired mutations in maize through hybridization and subsequent backcrossing, and hence bypassing the linkage drag effect in convention introgression methodology. This proof‐of‐concept experiment can be a potentially much more efficient breeding strategy in crops employing the RNA‐guided Cas9 genome editing.

Species-specific density is an essential parameter for evaluating population stability and ecosystem health. We estimate the population density of native carnivores, South American gray and culpeo foxes ( spp.), guiña ( ) and Andes skunk ( ), in central Chile, inferring on the potential influence of the availability of introduced exotic prey on their population dynamics. Monitoring with camera traps was conducted from March 1, 2021, to March 31, 2022, across three distinct landscapes representative of the coastal mountain range of central Chile: Mediterranean coastal thorn forest, Mediterranean coastal sclerophyllous forest, and exotic monoculture tree plantations. We estimated density using an R package, cameratrapR, where animal movement was simulated using a correlated random walk within the camera grids. Simulations were run for a range of numbers of individuals, representing a gradient of population densities. We matched these results and the observed photo records using a machine learning algorithm, random forest, thereby estimating population density and its 95% confidence intervals. A total of 10,046 trap days resulted in 9,120 photographs of carnivores, with 3,888 independent records. Our findings indicate that spp. are the carnivore species with the highest population density in central Chile (4.1-4.8 individuals/km ). Furthermore, their density was higher in the exotic monoculture tree plantation ecotype compared to native forests, suggesting a dietary subsidy from non-native prey. We report the first population density estimates for (1.8-2.2 individuals/km ) and (0.7-1.3 individuals/km ) in the three landscapes, showing different habitat preferences and resource availabilities across landscapes. The results highlight the complex interactions between carnivores and their environments, particularly the role of exotic introduced species as prey items in shaping native carnivore populations. These findings also provide insights into carnivore adaptability and the implications for biodiversity conservation.

Maize ( Zea mays ) is one of the most important food crops in the world with the greatest global production, and contributes to satiating the demands for human food, animal feed, and biofuels. With population growth and deteriorating environment, efficient and innovative breeding strategies to develop maize varieties with high yield and stress resistance are urgently needed to augment global food security and sustainable agriculture. CRISPR-Cas-mediated genome-editing technology (clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated)) has emerged as an effective and powerful tool for plant science and crop improvement, and is likely to accelerate crop breeding in ways dissimilar to crossbreeding and transgenic technologies. In this review, we summarize the current applications and prospects of CRISPR-Cas technology in maize gene-function studies and the generation of new germplasm for increased yield, specialty corns, plant architecture, stress response, haploid induction, and male sterility. Optimization of gene editing and genetic transformation systems for maize is also briefly reviewed. Lastly, the challenges and new opportunities that arise with the use of the CRISPR-Cas technology for maize genetic improvement are discussed.

Background Dorper and Tan sheep are renowned for their rapid growth and exceptional meat quality, respectively. Previous research has provided evidence of the impact of gut microbiota on breed characteristics. The precise correlation between the gastrointestinal tract and peripheral organs in each breed is still unclear. Investigating the metabolic network of the intestinal organ has the potential to improve animal growth performance and enhance economic benefits through the regulation of intestinal metabolites. Results In this study, we identified the growth advantage of Dorper sheep and the high fat content of Tan sheep. A transcriptome study of the brain, liver, skeletal muscle, and intestinal tissues of both breeds revealed 3,750 differentially expressed genes (DEGs). The genes PPARGC1A , LPL , and PHGDH were found to be highly expressed in Doper, resulting in the up-regulation of pathways related to lipid oxidation, glycerophospholipid metabolism, and amino acid anabolism. Tan sheep highly express the BSEP , LDLR , and ACHE genes, which up-regulate the pathways involved in bile transport and cholesterol homeostasis. Hindgut content analysis identified 200 differentially accumulated metabolites (DAMs). Purines, pyrimidines, bile acids, and fatty acid substances were more abundant in Dorper sheep. Based on combined gene and metabolite analyses, we have identified glycine, serine, and threonine metabolism, tryptophan metabolism, bile secretion, cholesterol metabolism, and neuroactive ligand-receptor interaction as key factors contributing to the differences among the breeds. Conclusions This study indicates that different breeds of sheep exhibit unique breed characteristics through various physiological regulatory methods. Dorper sheep upregulate metabolic signals related to glycine, serine, and threonine, resulting in an increase in purine and pyrimidine substances. This, in turn, promotes the synthesis of amino acids and facilitates body development, resulting in a faster rate of weight gain. Tan sheep accelerate bile transport, reduce bile accumulation in the intestine, and upregulate cholesterol homeostasis signals in skeletal muscles. This promotes the accumulation of peripheral and intramuscular fat, resulting in improved meat quality. This work adopts a joint analysis method of multi-tissue transcriptome and gut metabolome, providing a successful case for analyzing the mechanisms underlying the formation of various traits.

Nonribosomal peptides (NRPs) are biosynthesized by nonribosomal peptide synthetases (NRPSs) and are widely distributed in both terrestrial and marine organisms. Many NRPs and their analogs are biologically active and serve as therapeutic agents. The adenylation (A) domain is a key catalytic domain that primarily controls the sequence of a product during the assembling of NRPs and thus plays a predominant role in the structural diversity of NRPs. Engineering of the A domain to alter substrate specificity is a potential strategy for obtaining novel NRPs for pharmaceutical studies. On the basis of introducing the catalytic mechanism and multiple functions of the A domains, this article systematically describes several representative NRPS engineering strategies targeting the A domain, including mutagenesis of substrate-specificity codes, substitution of condensation-adenylation bidomains, the entire A domain or its subdomains, domain insertion, and whole-module rearrangements.

Nitrate is the major source of nitrogen available for many crop plants and is often the limiting factor for plant growth and agricultural productivity especially for maize. Many studies have been done identifying the transcriptome changes under low nitrate conditions. However, the microRNAs (miRNAs) varied under nitrate limiting conditions in maize has not been reported. MiRNAs play important roles in abiotic stress responses and nutrient deprivation. In this study, we used the SmartArray™ and GeneChip® microarray systems to perform a genome-wide search to detect miRNAs responding to the chronic and transient nitrate limiting conditions in maize. Nine miRNA families (miR164, miR169, miR172, miR397, miR398, miR399, miR408, miR528, and miR827) were identified in leaves, and nine miRNA families (miR160, miR167, miR168, miR169, miR319, miR395, miR399, miR408, and miR528) identified in roots. They were verified by real time stem loop RT-PCR, and some with additional time points of nitrate limitation. The miRNAs identified showed overlapping or unique responses to chronic and transient nitrate limitation, as well as tissue specificity. The potential target genes of these miRNAs in maize were identified. The expression of some of these was examined by qRT-PCR. The potential function of these miRNAs in responding to nitrate limitation is described. Genome-wide miRNAs responding to nitrate limiting conditions in maize leaves and roots were identified. This provides an insight into the timing and tissue specificity of the transcriptional regulation to low nitrate availability in maize. The knowledge gained will help understand the important roles miRNAs play in maize responding to a nitrogen limiting environment and eventually develop strategies for the improvement of maize genetics.

Pedestrian trajectory prediction poses significant challenges for autonomous systems due to the intricate nature of social interactions in densely populated environments. While the existing methods frequently encounter difficulties in effectively quantifying the nuanced social relationships, we propose a novel dual social graph attention network (DSGAT) that systematically models multi-level interactions. This framework is specifically designed to enhance the extraction of pedestrian interaction features within the environment, thereby improving the trajectory prediction accuracy. The network architecture consists of two primary branches, namely an individual branch and a group branch, which are responsible for modeling personal and collective pedestrian behaviors, respectively. For individual feature modeling, we propose the Spatio-Temporal Weighted Graph Attention Network (STWGAT) branch, which incorporates a newly developed directed social attention function to explicitly capture both the direction and intensity of pedestrian interactions. This mechanism enables the model to more effectively represent the fine-grained social dynamics. Subsequently, leveraging the STWGAT’s processing of directed weighted graphs, the network’s ability to aggregate spatiotemporal information and refine individual interaction representations is further strengthened. To effectively account for the critical group dynamics, a dedicated group attention function is designed to identify and quantify the collective behaviors within pedestrian crowds. This facilitates a more comprehensive understanding of the complex social interactions, leading to an enhanced trajectory prediction accuracy. Extensive comparative experiments conducted on the widely used ETH and UCY benchmark datasets demonstrate that the proposed network consistently surpasses the baseline methods across the key evaluation metrics, including the Average Displacement Error (ADE) and Final Displacement Error (FDE). These results confirm the effectiveness and robustness of the DSGAT-based approach in handling complex pedestrian interaction scenarios.

Heterosis contributes a big proportion to hybrid performance in maize, especially for grain yield. It is attractive to explore the underlying genetic architecture of hybrid performance and heterosis. Considering its complexity, different from former mapping method, we developed a series of linear mixed models incorporating multiple polygenic covariance structures to quantify the contribution of each genetic component (additive, dominance, additive-by-additive, additive-by-dominance, and dominance-by-dominance) to hybrid performance and midparent heterosis variation and to identify significant additive and non-additive (dominance and epistatic) quantitative trait loci (QTL). Here, we developed a North Carolina II population by crossing 339 recombinant inbred lines with two elite lines (Chang7-2 and Mo17), resulting in two populations of hybrids signed as Chang7-2 × recombinant inbred lines and Mo17 × recombinant inbred lines, respectively. The results of a path analysis showed that kernel number per row and hundred grain weight contributed the most to the variation of grain yield. The heritability of midparent heterosis for 10 investigated traits ranged from 0.27 to 0.81. For the 10 traits, 21 main (additive and dominance) QTL for hybrid performance and 17 dominance QTL for midparent heterosis were identified in the pooled hybrid populations with two overlapping QTL. Several of the identified QTL showed pleiotropic effects. Significant epistatic QTL were also identified and were shown to play an important role in ear height variation. Genomic selection was used to assess the influence of QTL on prediction accuracy and to explore the strategy of heterosis utilization in maize breeding. Results showed that treating significant single nucleotide polymorphisms as fixed effects in the linear mixed model could improve the prediction accuracy under prediction schemes 2 and 3. In conclusion, the different analyses all substantiated the different genetic architecture of hybrid performance and midparent heterosis in maize. Dominance contributes the highest proportion to heterosis, especially for grain yield, however, epistasis contributes the highest proportion to hybrid performance of grain yield.

The harvest index for many crops can be improved through introduction of dwarf stature to increase lodging resistance, combined with early maturity. The inbred line Shen5003 has been widely used in maize breeding in China as a key donor line for the dwarf trait. Also, one major quantitative trait locus (QTL) controlling plant height has been identified in bin 5.05-5.06, across several maize bi-parental populations. With the progress of publicly available maize genome sequence, the objective of this work was to identify the candidate genes that affect plant height among Chinese maize inbred lines with genome wide association studies (GWAS). A total of 284 maize inbred lines were genotyped using over 55,000 evenly spaced SNPs, from which a set of 41,101 SNPs were filtered with stringent quality control for further data analysis. With the population structure controlled in a mixed linear model (MLM) implemented with the software TASSEL, we carried out a genome-wide association study (GWAS) for plant height. A total of 204 SNPs (P≤0.0001) and 105 genomic loci harboring coding regions were identified. Four loci containing genes associated with gibberellin (GA), auxin, and epigenetic pathways may be involved in natural variation that led to a dwarf phenotype in elite maize inbred lines. Among them, a favorable allele for dwarfing on chromosome 5 (SNP PZE-105115518) was also identified in six Shen5003 derivatives. The fact that a large number of previously identified dwarf genes are missing from our study highlights the discovery of the consistently significant association of the gene harboring the SNP PZE-105115518 with plant height (P=8.91e-10) and its confirmation in the Shen5003 introgression lines. Results from this study suggest that, in the maize breeding schema in China, specific alleles were selected, that have played important roles in maize production.